Pozovnikova МV, Tulinova OV, Vasileva OK, Shcherbakov YuS.

Animal Husbandry and Fodder Production. 2024. Vol. 107, no 4. Р. 68-82.

 

doi:10.33284/2658-3135-107-4-68

 

Original article

Identification and GWAS analysis of significant genomic loci associated with mastitis resistance

in Ayrshire cows

 

Marina V Pozovnikova1, Olga V Tulinova2, Olga K Vasileva3, Yuriy S Shcherbakov4

1,2,3,4 Russian Research Institute of Farm Animal Genetics and Breeding – Branch of the L.K. Ernst Federal Research Center for Animal Husbandry, Tyarlevo, Russia

1pozovnikova@gmail.com, https://orcid.org/0000-0002-8658-2026

2tulinova_59@mail.ru, https://orcid.org/0009-0005-5704-4420

3vaciola@mail.ru, https://orcid.org/0000-0001-8361-8399

4yura.10.08.94.94@mail.ru, https://orcid.org/0000-0001-6434-6287

 

 Abstract. One of the methods for preventing the spread of subclinical mastitis in herds is the selection of animals with natural resistance to this disease. This approach is based on genetic predisposition, which determines the individual resistance of cows to various forms of mastitis. The aim of the study was to identify and analyze genomic regions and SNPs presumably associated with the somatic cell count, taking into account their differentiation in the Russian population of Ayrshire cows. The study included 5828 milk and DNA samples from 600 Ayrshire cows from six farms in the Leningrad and Moscow regions. On average, the SCC value was 184.1±12.1 thousand units/ml with fluctuations from 107.6±6.4 thousand units/ml to 272.5±49.4 thousand units/ml. A similar picture was observed in relation to the DSCC indicator with an average value of 31.8±0.7%, a minimum of 25.9±0.8% and a maximum of 47.9±4.2%. The heritability coefficients were calculated for the SCC – 0.207, for the DSCC – 0.085. A significant influence of the factors “Farm”, “Father” and “Lactation period” (p˂0.001) on the level of SCC and DSCC in cows’ milk was revealed. In the course of the study, using the Illumina BovineSNP50 BeadChip DNA chip, SNP profiles of animals were obtained and functional candidate genes were identified. GWAS analysis revealed three SNPs in BTA12 (MYO16, rs42775315), BTA17 (NELL1, rs43178042) and BTA29 (the closest region of the SCLT gene, rs43178042) significantly associated with the number of somatic cells in cows' milk (p < 0.00001). Animals with homozygous genotypes for rs42775315 GG (90.3%, 163.1±9.8 thousand units/ml), rs109897445 GG (44.17%, 137.5±11.6 thousand units/ml) and rs43178042 CC (85.0%, 162.6±9.5 thousand units/ml) had lower SCC values. The results obtained provide important information on the genetic mechanisms that determine the predisposition to mastitis in Ayrshire cows.

Keywords: cows, Ayrshire breed, milk, somatic cells, SNP, candidate gene, DNA-chip

Acknowledgments: the work was performed in accordance to the plan of research works for 2024 FSBRI Federal Research Center for Animal Husbandry named after Academy Member L.K. Ernst (No. FGGN-2024-0021).

For citation: Pozovnikova МV, Tulinova OV, Vasileva OK, Shcherbakov YuS. Identification and GWAS analysis of significant genomic loci associated with mastitis resistance in Ayrshire cows. Animal Husbandry and Fodder Production. 2024;107(4):68-82. (In Russ.). https://doi.org/10.33284/2658-3135-107-4-68

 

References

 
  1. Bolgov AE, Komlyk IP, Grishina NV. Determination and use of bulls breeding value indices for somatic milk cells in daughters during selection for mastitis resistance. Genetics and Breeding of Animals. 2020;1:3-8. doi: 31043/2410-2733-2020-1-3-8
  2. Pozovnikova MV, Leibova VB, Tulinova OV, Romanova EA, Shcherbakov YuS. Effect of the somatic cell count, taking into account their morphological differentiation, on the component composition of cow’s milk. Russian Agricultural Sciences. 2022;6:57-62. doi:31857/S2500262722060114
  3. Sychyova IN, Orishev AB, Mamedov A A, Ivashova ON, Muslyumova DM. Effect of elemental status correction on the quantitative and qualitative characteristics of milk in dairy cows. Animal Husbandry and Fodder Production. 2022;105(3):8-18. doi: 33284/2658-3135-105-3-8
  4. Bolgov AE, Komlyk IP, Grishina NV, Patalainen LS. Age and hereditary factors of somatic cells number variability in milk of Ayrshire cows. Genetics and Breeding of Animals. 2019;2:36-41. doi: 10.31043/2410-2733-2019-2-36-41
  5. State Standard R 52054-2003 Cow's milk raw. Specifications. Implementation date05.2003. Moscow: Standartinform; 2008:30 p.
  6. Lashneva IA. Genetic and genomic variability of milk component composition and somatic cell count in Holstein cows. [dissertation] Dubrovicy; 2023:206 p.
  7. Naimanov DK, Shaykamal GI, Kazhiyakbarova AT, Dzulamanov EB. Milk productivity of daughters from sires of various lines of Hholstein breed and the content of somatic cells in milk. Animal Husbandry and Fodder Production. 2019;102(2):115-124. doi: 10.33284/2658-3135-102-2-115
  8. Sermyagin AA, Lashneva IA, Kositsin AA, Ignatieva LP, Artemieva OA, Sölkner J, Zinovieva N.A. Differential somatic cell count in milk as criteria for assessing cows’ udder health in relation with milk production and components. Sel'skokhozyaistvennaya Biologiya [Agricultural Вiology]. 2021;56(6):1183-1198. doi: 10.15389/agrobiology.2021.6.1183rus  doi: 10.15389/agrobiology.2021.6.1183eng
  9. Kostomakhin NM, Tabakov GP, Tabakova LP, Nikitchenko VYe, Korotkov AS. Morphofunctional properties of udder, conformation features and milk productivity of different cow breeds. Izvestiya of Timiryazev Agricultural Academy. 2020;2:64-84. doi: 10.26897/0021-342X-2020-2-64-84
  10. Isakova MN, Ryaposova MV, Mymrin SV, Sivkova UV. Determination of urea in the milk of highly productive cows – a prognostic marker of mastitis development. Animal Husbandry and Fodder Production. 2021;104(3):147-154. doi: 33284/2658-3135-104-3-147
  11. Tretyakov YeA. Milk quality of Ayrshire breed cows (Prilutsky type) depending on a season and a keeping way. Dairy Bulletin. 2018;2(30):89-97.
  12. Ablondi M, Summer A, Stocco G, Degano L, Vicario D, Stefanon B, Cipolat-Gotet C. Heritability and  genetic  correlations  of  total  and  differential  somatic  cell  count  with  milk  yield  and  composition  traits  in  Italian  Simmental cows. Journal of Dairy Science. 2023;106(12):9071-9077. doi: 3168/jds.2023-23639
  13. Artemieva O, Nikanova DA, Kositsin A, Lashneva I, Ignatieva LP, Sermyagin AA, Zinovieva NA. PSX-B-21 Diagnosis of early mastitis in dairy cows: Somatic cells and bacterial pathogen measuring. Journal of Animal Science. 2021;99(3):269-270. doi: 10.1093/jas/skab235.494
  14. Cai Z, Iso-Touru T, Sanchez MP, Kadri N, Bouwman AC, Chitneedi PK, Sahana G, et al. Meta-analysis of six dairy cattle breeds reveals biologically relevant candidate genes for mastitis resistance. Genetics Selection Evolution. 2024;56(1):54. doi: 10.1186/s12711-024-00920-8
  15. Chen H, Zhang Z, Zhang L, Wang J, Zhang M, Zhu B. miR-27a protects human mitral valve interstitial cell from TNF-α-induced inflammatory injury via up-regulation of NELL-1. Brazilian Journal of Medical and Biological Research. 2018;51(6):e6997. doi: 1590/1414-431X20186997
  16. Duchemin SI, Bovenhuis H, Megens HJ, Van Arendonk JAM, Visker MHPW. Fine-mapping of BTA17 using imputed sequences for associations with de novo synthesized fatty acids in bovine milk. Journal of Dairy Science. 2017;100(11):9125-9135. doi: 3168/jds.2017-12965
  17. Huang CH, Furukawa K, Kusaba N, Baba T, Kawakami J, Hagiya K. Genetic parameters for novel  mastitis  traits  defined  by  combining  test-day  somatic  cell score and differential somatic cell count in the first lactation of Japanese Holsteins. Journal of Dairy Science. 2024;107(6):3738-3752. doi:3168/jds.2023-24399
  18. Kaczorowski Ł, Powierska-Czarny J, Wolko Ł, Piotrowska-Cyplik A, Cyplik P, Czarny J. The influence of bacteria causing subclinical mastitis on the structure of the cow’s milk microbiome. Molecules. 2022;27(6):1829. doi: 3390/molecules27061829
  19. Kiser JN, Neibergs HL. Identifying loci associated with bovine corona virus infection and bovine respiratory  disease  in  dairy  and  feedlot    Front  Vet  Sci. 2021;8:679074. doi: 10.3389/fvets.2021.679074
  20. Misztal I, Tsruta S, Strabel T, Auvray B, Druet T, Lee DH. BLUPF90 and related programs (BGF90). Proceedings of the 7th world congress on genetics applied to livestock production. France, Montpellier, 19-23 Aug. Communication. 2002;28-07(28):21-22.
  21. Narayana SG, de Jong E, Schenkel FS, Fonseca PA, Chud TC, Powell D, Barkema HW, et al. Underlying genetic architecture of resistance to mastitis in dairy cattle: A systematic review and gene prioritization analysis of genome-wide association studies. Journal of Dairy Science. 2023;106(1):323-351. doi: 10.3168/jds.2022-21923
  22. Nazar M, Lu X, Abdalla IM, Ullah N, Fan Y, Chen Z, Yang Z, et al. Genome-wide association study candidate genes on mammary system-related teat-shape conformation traits in Chinese Holstein cattle. Genes. 2021;12(12):2020. doi: 3390/genes12122020
  23. Ott CM. Primary Cilia. Arais IM, et al. The Liver: Biology and Pathobiology, 6 th edition. 2020:50-61. doi: 1002/9781119436812.ch5
  24. Rakib MRH, Zhou M, Xu S, Liu Y, Khan MA, Han B, Gao J. Effect of heat stress on  udder  health of dairy cows. Journal of Dairy Research. 2020;87(3):315-321. doi:  1017/S0022029920000886
  25. Ravi Kumar D, Nandhini PB, Joel Devadasan M, Sivalingam J, Mengistu D W, Verma A, Tantia MS, et al. Genome-wide association study revealed suggestive QTLs for production and reproduction traits in Indian Murrah buffalo. 3 Biotech. 2023;13(3):100. doi: 10.1007/s13205-023-03505-2
  26. Schwarz D, Kleinhans S, Reimann G, et al. Investigation of dairy cow performance in different udder health groups defined based on a combination of somatic cell count and differential somatic cell count. Preventive Veterinary Medicine. 2020;183:105123. doi: 10.1016/j.prevetmed.2020.105123
  27. Shen J, James AW, Zara JN, Asatrian G, Khadarian K, Zhang JB, Soo C, et al. BMP2-induced inflammation can be suppressed by the osteoinductive growth factor NELL-1. Tissue engineering Part A. 2013;19(21-22):2390-2401. doi: 1089/ten.tea.2012.0519
  28. Telek E, Karadi K, Kardos J, Kengyel A, Fekete Z, Halasz H, Lukacs A, et al. Conformational dynamics and functional characterization of the C-terminal tail of Myosin 16. Biophysical Journal. 2022;121(3-1):181a. doi:1016/j.bpj.2021.11.1831
  29. Zhang Y, Xu Y, Chen B, Zhao B, Gao XJ. Selenium deficiency promotes oxidative stress-induced mastitis via activating the NF-κB and MAPK pathways in dairy cow. Biological Trace Element Research. 2022;200(6):2716-2726. doi: 10.1007/s12011-021-02882-0
 

Information about the authors:

Marina V Pozovnikova, Cand. Sci. (Biology), Senior Researcher Laboratories of Molecular Genetics, Russian Research Institute of Farm Animal Genetics and Breeding – Branch of the L.K. Ernst Federal Research Center for Animal Husbandry, St. Petersburg, Tyarlevo, Moscow highway, 55a, 196601, tel.: +7-960-231-03-21.

Olga V Tulinova, Cand. Sci. (Agriculture), Leading Researcher Laboratory of Genetics and Cattle Breeding, Russian Research Institute of Farm Animal Genetics and Breeding – Branch of the L.K. Ernst Federal Research Center for Animal Husbandry, St. Petersburg, Tyarlevo, Moscow highway, 55a, 196601, tel.: +7-921-305-80-06.

Olga K Vasileva, Cand. Sci. (Agriculture), Researcher Laboratory of Genetics and Cattle Breeding, Russian Research Institute of Farm Animal Genetics and Breeding – Branch of the L.K. Ernst Federal Research Center for Animal Husbandry, St. Petersburg, Tyarlevo, Moscow highway, 55a, 196601, tel.: +7-911-280-78-81.

Yuriy S Shcherbakov, Cand. Sci. (Biology), Junior Researcher Laboratories of Molecular Genetics, Russian Research Institute of Farm Animal Genetics and Breeding – Branch of the L.K. Ernst Federal Research Center for Animal Husbandry, St. Petersburg, Tyarlevo, Moscow highway, 55a, 196601, tel.: +7-999-524-47-84

 

The article was submitted 02.10.2024; approved after reviewing 11.11.2024; accepted for publication 16.12.2024.

Download